R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1145,1057,1218,1146,1150,983,1013,960,925,1087,1063,1049,1153,972,1111,985,1005,820,976,982,960,842,1008,1086,1207,958,1040,800,886,906,892,908,1025,1108,1097,1074,981,920,1065,994,1021,864,864,837,920,1085,1048,1112,1080,1140,1159,1044,871,807,1110,1078,1079,1247,1136,1066,1073,976,1073,1144,1023,694,1052,1124,1104,1183,1320,1227)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/17y9d1425587345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2uja21425587345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3a5x21425587345.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.439494569  0.181124743 -0.038165255 -0.086815356
 [6] -0.233077653 -0.145775491 -0.077208454  0.006848104  0.144325912
[11]  0.259036864  0.162403783  0.361298429  0.171143720  0.109967659
[16] -0.077906340 -0.076619487 -0.227927034 -0.285005665 -0.163241506
[21] -0.007432976  0.125091476  0.242897470  0.173473656  0.175787419
[26] -0.005923361 -0.080449253 -0.293314661 -0.256418216 -0.263816746
[31] -0.187710079 -0.058328457 -0.065924000 -0.022127338  0.048413342
[36]  0.093967718  0.096860718 -0.008320406 -0.008483362 -0.189528116
[41] -0.212439934 -0.311397833 -0.227121917 -0.106057178  0.038668590
[46]  0.115485473  0.094037106  0.100492991  0.076157056
> (mypacf <- c(rpacf$acf))
 [1]  0.439494569 -0.014910845 -0.139341976 -0.021729177 -0.202261782
 [6]  0.039542809  0.009289792  0.005630428  0.159213555  0.126833369
[11] -0.052666286  0.398224361 -0.142960568  0.115708727 -0.024821728
[16] -0.063719796 -0.060587651 -0.243327422  0.028397509  0.039933874
[21] -0.027041998  0.084800948 -0.048751112 -0.013392863 -0.018733696
[26] -0.139744263 -0.077796510 -0.048995233 -0.129083075  0.057473580
[31] -0.019523371 -0.247552189  0.024138189 -0.092928963  0.049385297
[36]  0.062473318 -0.083887695  0.190663535 -0.051434547 -0.064250989
[41] -0.029775170 -0.072901903 -0.019456536  0.113043659 -0.136156555
[46]  0.017573707  0.023969661 -0.047570534
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 2:(par1+1)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-1,header=TRUE)
+ a<-table.element(a,round(myacf[i],6))
+ mytstat <- myacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4py1v1425587345.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:par1) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(mypacf[i],6))
+ mytstat <- mypacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5kmxj1425587345.tab") 
> 
> try(system("convert tmp/17y9d1425587345.ps tmp/17y9d1425587345.png",intern=TRUE))
character(0)
> try(system("convert tmp/2uja21425587345.ps tmp/2uja21425587345.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a5x21425587345.ps tmp/3a5x21425587345.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.242   0.229   1.475